7 Big Data Solutions Try To Reshape Healthcare

Big data medicine is still largely unproven, but that's not stopping several medical centers and analytics vendors from jumping in with both feet.

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Clinical Query might not have the same profit motive as commercially available big data companies, but it can certainly hold its own in the race to squeeze intelligence from mountains of untapped medical data.

Clinical Query, a medical informatics platform in use at Beth Israel Deaconess Medical Center, was designed to improve quality while reducing costs. To accomplish these twin goals, clinicians need to focus not only on the care of the patients sitting in front of them, but also the larger population with the same disease or condition -- so-called population health management. That mandate requires data analytics tools that are much more sophisticated than most.

Enter Clinical Query. John Halamka, BIDMC's CIO, refers to it as a clinical trials/clinical research business intelligence system. It's a search engine married to a huge database of patient records that lets hospital employees test hypotheses about what causes a disease, for instance, or test which drug, diet or lifestyle variables might reduce the risk of developing one.

The repository contains 200 million data points on 2.2 million patients, including medications taken, diagnoses and lab values. The query tool is capable of navigating 20,000 medical concepts through the use of Boolean expressions. All the data has been mapped to standard medical language codes. Diagnoses, for instance, have been mapped to ICD-9; medications to RxNorm codes; and lab data to Logical Observation Identifiers Names and Codes (LOINC).

With the help of Clinical Query, a clinician or researcher might, for instance, search the records to find out how many patients with breast cancer also take ACE inhibitors, a class of drugs used to treat high blood pressure. If the results reveal a strong correlation between the drug and the malignancy, the hospital could do a deeper analysis and set up a formal research project to investigate the link.

The ultimate goal would be to discover a new medical intervention that would improve the survival of the entire population of breast cancer patients.

"What's unique about Clinical Query is that it's completely self-service," Halamka said. "I didn't have to go out and hire an analyst. I didn't have to get special permission to get access or approval from our [institutional review board] to use it."

This is definitely a unique somewhat new technoloy, however, it is very important that we learn how effective and accurate the information is. I have been reading about the technology and researching fo the past five months. One new company, I find to be intersting is Due North Analytics.

They are a start up but seem to have an advantage. They provide cutting edge analytics for healthcare institutions. They totally understand the importance of Big Data for the industry. They started their company knowing they could help Healthcare institutions do three things.

1 Predict potential rates, so they can predict the fluctuation of symptoms and plan accordingly with staffing, equipment and insurance rates. 2. Predict patient trends so that they can understand what diseases the patients may be vulnerable to in the future. 3. Determine the effectiveness of medication. Knowing what is working and not working could save patients, hospitals, and insurance companies a lot of money. Check out their website I know you will be impressed with their capabilities.

During my interviews with Big Data vendors and medical centers, I did see some tangible results, but in some cases they were improvements in "intermediate endpoints," as medical researchers like to phrase it.

Improvements in blood glucose or serum cholesterol levels in patients whose data has been crunched is worthwhile, but it's not the same as documented evidence that the analysis reduced cardiac deaths or limb amputations. Those are the real endpoints we need to reach.Paul CerratoEditorInformationWeek Healthcare